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Quanvier
AI solutions

AI as a business capability, not a buzzword.

We build AI products that answer from your data, take approved actions in your systems, and get measurably better — with people in control of what matters.

Hi! Where is my order #NW-48213? It's a gift for Saturday.
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How we build AI

Six rules we don't bend.

01

Grounded, not guessing

Answers come from your approved data with citations. No evidence, no answer.

02

Tools with permissions

Agents act through typed tools with scoped access, spend limits and audit logs.

03

Humans where it matters

Confidence and policy thresholds decide when a person approves.

04

Measured with evals

Every prompt, model or retrieval change is scored against real examples before release.

05

Model-agnostic

Claude, GPT or open-source — chosen per task for quality, latency and cost.

06

Private by design

Providers that don't train on your data, PII redaction, and in-cloud deployment when needed.

Inputs
Chat / WhatsApp
Email & documents
Events & webhooks
Orchestration
Router
Policy & guardrails
Prompt templates
Intelligence
Retriever (hybrid)
LLM
Tool executor
Control
Human approval
Eval suite
Tracing & cost
Systems
CRM / ERP
Databases
Payments
Simplified architecture · request flow left → right
01 · AI product

AI Support Agent

Handles customer questions using company knowledge and live order data.

Problem
Most support volume is repetitive — order status, returns, policies — yet each answer needs live data from another system.
Product
An agent that retrieves from approved sources, calls order and shipping tools, cites what it used and drafts or sends based on confidence.
How the AI works
  • Hybrid retrieval over help center, policies and docs
  • Typed tools for order lookup, tracking and refunds
  • Policy checks before any action
  • Confidence threshold decides send vs. draft vs. escalate
Workflow
  1. Question arrives on chat, WhatsApp or email
  2. Agent retrieves knowledge and calls tools
  3. Drafts a cited answer
  4. Auto-sends or queues for approval
  5. Logs outcome for evaluation
Benefits
  • Faster first response
  • Humans focus on complex cases
  • Consistent, policy-correct answers
  • Clear list of documentation gaps
Integrates with
ShopifyZendeskFreshdeskWhatsAppIntercom
02 · AI product

AI Sales Assistant

Analyses leads and deal activity and recommends the next action.

Problem
Reps spend time on data entry and research; managers find out deals are stalling when it's too late.
Product
A copilot inside the CRM that summarises threads, scores deal health and proposes concrete next steps with drafts ready.
How the AI works
  • Ingests email, calendar and call notes
  • Scores engagement and stakeholder coverage
  • LLM summarises and proposes actions
  • Rep approves, edits or dismisses
Workflow
  1. New activity on a deal
  2. Signals recomputed
  3. Copilot suggests next best action
  4. Rep sends the draft or schedules the task
Benefits
  • Less admin per rep
  • Earlier warning on risky deals
  • Better-prepared meetings
  • Forecasts grounded in activity
Integrates with
HubSpotSalesforceGoogle WorkspaceMicrosoft 365LinkedIn (manual)
03 · AI product

AI Document Intelligence

Extracts and validates information from invoices, contracts, KYC and claims.

Problem
Teams re-type fields from PDFs and scans into systems, then find errors weeks later.
Product
A pipeline that classifies documents, extracts fields and tables, validates against business rules and routes uncertain ones to people.
How the AI works
  • OCR + vision-language extraction
  • Structured outputs with per-field confidence
  • Rules: PO match, duplicates, tax arithmetic
  • Review UI with source highlighting
Workflow
  1. Document arrives by email or upload
  2. Classified and extracted
  3. Validated against rules and master data
  4. Posted to ERP or queued for review
Benefits
  • Data entry becomes data review
  • Errors caught at intake
  • Full audit trail
  • Scales with volume, not headcount
Integrates with
TallyZoho BooksSAPGoogle DriveIMAP inboxes
04 · AI product

AI Knowledge Assistant

Lets employees search internal knowledge in plain language.

Problem
Answers live in Notion, Drive, Confluence and Slack threads; people ask colleagues instead of searching.
Product
An internal assistant that respects document permissions, answers with citations and links back to the source.
How the AI works
  • Connectors index docs with their access control lists
  • Permission-aware retrieval per user
  • Answers cite and link sources
  • Feedback loop flags stale content
Workflow
  1. Employee asks in Slack or web
  2. Assistant retrieves what that user may see
  3. Answers with sources
  4. Feedback improves ranking
Benefits
  • Faster onboarding
  • Fewer interruptions for experts
  • Stale docs surfaced
  • Knowledge stays inside your boundary
Integrates with
SlackMicrosoft TeamsNotionConfluenceGoogle DriveSharePoint
05 · AI product

AI Workflow Agent

Automates multi-step business workflows across systems.

Problem
Processes like vendor onboarding or refund handling hop across five systems and stall in inboxes.
Product
An agent that follows a defined playbook, calls tools step by step, and pauses for human approval at the points you choose.
How the AI works
  • Workflow defined as explicit steps and tools
  • LLM handles unstructured inputs between steps
  • Approval gates and spend limits
  • Every step logged and replayable
Workflow
  1. Trigger (email, form, webhook)
  2. Agent gathers and checks data
  3. Approval gate when required
  4. Actions executed in systems
  5. Summary sent to owner
Benefits
  • Cycle time measured in minutes
  • Fewer dropped hand-offs
  • Consistent policy application
  • Auditable automation
Integrates with
Zapier / n8nInternal APIsEmailERPPayment gateways
06 · AI product

AI Analytics Copilot

Lets business users ask questions about company data.

Problem
Every new question becomes a ticket for the data team; dashboards answer last quarter's questions.
Product
A copilot that translates questions into SQL against a governed semantic layer, shows the query, and charts the result.
How the AI works
  • Semantic layer defines metrics and joins
  • LLM generates SQL against that layer only
  • Read-only execution with row limits
  • Query and assumptions shown alongside the answer
Workflow
  1. User asks a question
  2. Copilot maps to metrics
  3. Runs a safe read-only query
  4. Returns chart, table and explanation
Benefits
  • Self-serve answers
  • Consistent metric definitions
  • Data team focuses on modelling
  • Transparent, checkable results
Integrates with
PostgreSQLBigQuerySnowflakeMetabaseGoogle Sheets

Where could AI save your team real hours?

We start with a short assessment: which workflows, what data, what risk. Then we prove it with an evaluation before anything ships.

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